ICARUS: Modelling Human Falls for Forensics - Passive Models

DOI:10.4121/20054996.v1
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DOI: 10.4121/20054996

Datacite citation style

Arjo J. Loeve; Hutchinson, Kim; Mugge, Winfred; Zandwijk, Jan Peter van; de Vette, Vera (2024): ICARUS: Modelling Human Falls for Forensics - Passive Models. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20054996.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Falls are a significant cause of injury-associated deaths. In cases where the events leading up to a fall are unclear, a forensic investigation may be required to uncover the cause. During the forensic reconstruction process, tools for objective scenario-evaluation are needed. Computer simulations appear to be a promising tool for fall reconstruction, being cheaper in terms of both money and time than the alternative of physical scenario-reconstruction. Although software packages intended for modelling the kinetics and kinematics of the human body exist, none were found that were validated specifically for fall-reconstruction. The aim of the current study was to validate the performance of human body modelling software Madymo, intended for use in car-crash simulations, in reconstructing human falling movements. This was achieved by first performing experiments in which the kinematics and kinetics of participants were recorded during falls from a short height. Next, the initial conditions taken from the experimentally recorded falls were used as input to run corresponding simulations using Madymo. Finally, the results from the simulated falls were compared to those from the real falls, based on the posture just before landing. Our results suggest that Madymo is currently not yet suitable for use in reconstructing real human falls, and is therefore not yet fit for application in forensic investigations into falls.


This dataset provides all registered video, motion capture suit, simulations, data-processing code and processed data of this project.

History

  • 2024-06-03 first online, published, posted

Publisher

4TU.ResearchData

Format

code/py,m,sav,mat; image/jpg; Xsens data; SPSS data

Funding

  • Netherlands Forensic Institute

Organizations

TU Delft, Faculty of Mechanical Engineering, Department of BioMechanical Engineering;
Netherlands Forensic Institute (NFI)

DATA

Files (4)